Effective and Efficient Content Redundancy Detection of Web Videos

2019 ◽  
pp. 1-1
Author(s):  
Yixin Chen ◽  
Dongsheng Li ◽  
Yu Hua ◽  
Wenbo He
Keyword(s):  
Web Videos ◽  
Redundancy Detection

Minimum attribute reduction algorithm based on quick extraction and multi-strategy social spider optimization

2021 ◽  
pp. 1-16
Author(s):  
Qianjin Wei ◽  
Chengxian Wang ◽  
Yimin Wen
Keyword(s):  
Rough Set Theory ◽  
Attribute Reduction ◽  
Search Space ◽  
Initial State ◽  
Solution Quality ◽  
Social Spider ◽  
Opposition Based Learning ◽  
Social Spider Optimization ◽  
Intelligent Optimization Algorithm ◽  
Redundancy Detection

Intelligent optimization algorithm combined with rough set theory to solve minimum attribute reduction (MAR) is time consuming due to repeated evaluations of the same position. The algorithm also finds in poor solution quality because individuals are not fully explored in space. This study proposed an algorithm based on quick extraction and multi-strategy social spider optimization (QSSOAR). First, a similarity constraint strategy was called to constrain the initial state of the population. In the iterative process, an adaptive opposition-based learning (AOBL) was used to enlarge the search space. To obtain a reduction with fewer attributes, the dynamic redundancy detection (DRD) strategy was applied to remove redundant attributes in the reduction result. Furthermore, the quick extraction strategy was introduced to avoid multiple repeated computations in this paper. By combining an array with key-value pairs, the corresponding value can be obtained by simple comparison. The proposed algorithm and four representative algorithms were compared on nine UCI datasets. The results show that the proposed algorithm performs well in reduction ability, running time, and convergence speed. Meanwhile, the results confirm the superiority of the algorithm in solving MAR.

A Unified Geolocation Framework for Web Videos

2014 ◽  
Vol 5 (3) ◽  
pp. 1-22 ◽  
Author(s):  
Yicheng Song ◽  
Yongdong Zhang ◽  
Juan Cao ◽  
Jinhui Tang ◽  
Xingyu Gao ◽  
...  
Keyword(s):  
Web Videos

scholarly journals Combinatorial redundancy detection

2016 ◽  
Vol 265 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Komei Fukuda ◽  
Bernd Gärtner ◽  
May Szedlák
Keyword(s):  
Redundancy Detection

scholarly journals Learning From Web Videos for Event Classification

2018 ◽  
Vol 28 (10) ◽  
pp. 3019-3029 ◽  
Author(s):  
Nicolas Chesneau ◽  
Karteek Alahari ◽  
Cordelia Schmid
Keyword(s):  
Event Classification ◽  
Web Videos

scholarly journals Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues

2014 ◽  
Vol 29 (5) ◽  
pp. 785-798 ◽  
Author(s):  
Zhi-Neng Chen ◽  
Chong-Wah Ngo ◽  
Wei Zhang ◽  
Juan Cao ◽  
Yu-Gang Jiang
Keyword(s):  
Large Scale ◽  
Large Scale Dataset ◽  
Web Videos ◽  
Open Issues

scholarly journals Speaker trait characterization in web videos: Uniting speech, language, and facial features

2013 ◽  
Author(s):  
Felix Weninger ◽  
Claudia Wagner ◽  
Martin Wollmer ◽  
Bjorn Schuller ◽  
Louis-Philippe Morency
Keyword(s):  
Facial Features ◽  
Web Videos

Affective image operations

2016 ◽  
Author(s):  
Jens Eder
Keyword(s):  
Case Studies ◽  
Interdisciplinary Research ◽  
Theoretical Framework ◽  
Political Conflict ◽  
Stimulate Action ◽  
Political Force ◽  
Moving Images ◽  
Web Videos ◽  
War Propaganda ◽  
Affective Structure

Affective image operations are attempts to influence behaviour and stimulate action by evoking affects through images. The paper explores their forms and uses in political conflict, from video activism to war propaganda. Drawing together interdisciplinary research, the chapter develops a theoretical framework for analysing the affective and political force of still and moving images, arguing that the affective structure of images has four layers: Political affects and emotions are triggered by the specific interplay of visual forms, worlds, messages, and reflections. On the basis of this framework, several frequent types of affective image operations can be distinguished, illustrated by brief case studies of political web videos.

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